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Ruochen Zhao

Ruochen Zhao has 3 papers in our library, in 2023–2025, most of them on Reasoning, Language models & pretraining, Information retrieval & search; often with Lidong Bing, Shafiq Joty, Weiwen Xu.

3 papers in our library · 2023–2025

OpenAlex · h-index 1 · 4 works · 7 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 110 times in our library · ⭐ Paper Stars ranking: #5927

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Nanyang Technological UniversitySingapore · Singapore2024–2025 · 3 papers🏛️Agency for Science, Technology and ResearchSingapore · Singapore2024 · 2 papers🔬Institute of High Performance ComputingSingapore · Singapore2024 · 2 papers🎓Princeton UniversityPrinceton · United States2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 1 workInformation Systems · 2 works

🧭 Topics 3Research subjects and languages the work is about.Reasoning · 2 worksInformation retrieval & search · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20252 papers20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework (2023 · 145 citations)
    Large language models often invent facts. Chain-of-Thought (CoT) prompting makes their reasoning visible, but it does not fix this weakness on knowledge-heavy tasks. The authors propose Verify-and-Edit (VE), a framework built on GPT-3 that repairs reasoning chains after they are generated, rather than only choosing…
  2. Auto-Arena: Automating LLM Evaluations with Agent Peer Battles and Committee Discussions (2025 · 16 citations)
    Keeping up with rapidly released LLMs requires evaluation that is both fast and trustworthy. Static benchmarks such as MMLU or MT-Bench risk contamination and handle open-ended output poorly. Crowdsourced platforms like Chatbot Arena are trusted but need many human votes, which makes them slow for new models and weak…
  3. Can We Further Elicit Reasoning in LLMs? Critic-Guided Planning with Retrieval-Augmentation for Solving Challenging Tasks (2025 · 13 citations)
    LLMs that combine chain-of-thought with retrieval-augmented generation often fail on hard, knowledge-heavy problems such as competitive programming.

 Co-authors here

9 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 110 times (of the 149,439 papers whose bibliographies we read); 29 citing papers with a page here →.

Updated

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